SARS-Cov-2 proliferation: an analytical aggregate-level model

  1. Thomas Pitschel

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Abstract

An intuitive mathematical model describing the virus proliferation is presented and its parameters estimated from time series of observed reported CoViD-19 cases in Germany. The model replicates the main essential characteristics of the proliferation in a stylized form, and thus can support the systematic reasoning about interventional measures (or their lifting) that were discussed during summer and which currently become relevant again in some countries. The model differs in form from elementary SIR models, but is contained in the general Kermack-McKendrick (1927) model. It is maintained that (compared to elementary SIR models) the model is more faithfully representing real proliferation at the instantaneous level, leading to overall more plausible association of model parameters to physical transmission and recovery parameters. The main policy-oriented results are that (1) mitigation measures imposed in March 2020 in Germany were absolutely necessary to avoid health care resource exhaustion, (2) fast response is key to containment in case of renewed outbreaks. Two model generalizations aiming to better represent the true infectiousness profile and aiming to incorporate recurring susceptibility are stated and numerical results for the latter are presented.

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  1. ScreenIT

    SciScore for 10.1101/2020.08.20.20178301: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    No key resources detected.

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

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  2. Version published to 10.1101/2020.08.20.20178301 on medRxiv